1. Field of the Invention
The present invention relates, in general, to trend analysis and, more particularly, to trend analysis incorporated into the monitoring, processing, and output features of a sedation and analgesia system.
2. Description of the Related Art
A sedation and analgesia system was developed to provide patients undergoing painful, uncomfortable or otherwise frightening (anxiety inspiring) medical or surgical procedures with a means for receiving sedative, analgesic, and/or amnestic drugs safely in a way that reduces the risk of overmedication with or without the presence of a licensed anesthesia provider. Due to significant advances in technology, the sedation and analgesia system is safe for use in hospital and ambulatory environments and may be operated by individuals other than trained anesthesiologists such as, for example, C.R.N.A.'s, trained physicians, or other trained operators. The sedation and analgesia system has gone far to meet the needs of practitioners who are unable to schedule anesthesia providers for every procedure where safe and effective sedation and analgesia could substantially mitigate fear and pain. The advent of a sedation and analgesia system devoted to these purposes provides these individuals with a drug delivery system integrated into a patient monitoring system that decreases the cognitive and manual workload required with the operation of anesthesia machines, yet keeps the clinician in the loop of patient management. The clinician maintains ultimate decision making responsibility following a “clinician knows best” philosophy. This advanced technology allows for a sedation and analgesia system to be operated at drug level effects less than general anesthesia without an anesthesia provider, providing the patient with a cost-effective and readily available means of sedation, amnesia, and/or analgesia.
An example of a sedation and analgesia system is described in U.S. patent application Ser. No. 09/324,759, filed Jun. 3, 1999 and incorporated herein by reference in its entirety. This sedation and analgesia system electronically integrates, for example, the delivery of one or more sedative, analgesic, and/or amnestic drugs, the delivery of positive airway pressure, decreases or increases in drug delivery, the delivery of oxygen, changes in drugs to, for example, an opioid antagonist, requests for additional information from patient monitors, and the triggering of alarms, with the electronic monitoring of one or more patient physiological conditions. In one form, the system of the '759 application uses one or more sets of stored data-defining parameters reflecting patient and system states, the parameters being accessed through software to conservatively manage and correlate drug delivery to safe, cost effective, optimized values related to the conscious patient's vital signs and other physiological conditions.
Spurious monitored data or other factors may cause the sedation and analgesia system to take potentially hazardous action, to fail to take action in critical situations, or to alarm unnecessarily. For example, the sedation and analgesia system may be monitoring a patient's heart rate with an electrocardiograph (ECG) when the ECG becomes erratic. Based on the single monitor, the sedation and analgesia system may signal an alarm indicating, for example, a dangerously low heart rate, when the erratic ECG data is actually spurious. A high frequency of false positive alarms may annoy clinicians and may result in less attention being given to truly life-threatening conditions.
Generally, monitoring systems incorporated into medical devices monitor a given patient parameter with a dedicated monitor. Safe data sets are then established for the monitored parameter, where if monitored data falls outside of the safe range, alarm responses are initiated. Such systems may provide high sensitivity, where most true adverse patient conditions are detected, however, such systems may also be prone to false positive alarms that result from data artifact that falls outside of the safe data set. Further, many patient parameters, such as heart rate, in the event of an impending adverse patient condition will drop in a linear or monotonic fashion towards thresholds of the safe data set indicating an adverse patient condition. In existing monitoring systems, such a drop is generally not detected until the data is outside the safe data set; however, it may be apparent from viewing a patient's heart rate over time that an adverse patient event is imminent several seconds before the patient parameter actually drops out of the safe data set. Waiting until data crosses established safe data set thresholds may leave clinicians to play catch up in situations where a patient is already experiencing an adverse condition.